Shauloff Nitzan, Morag Ahiud, Yaniv Karin, Singh Seema, Malishev Ravit, Paz-Tal Ofra, Rokach Lior, Jelinek Raz
Department of Chemistry, Ben Gurion University of the Negev, 84105, Beer Sheva, Israel.
Department of Biotechnology Engineering, Ben Gurion University of the Negev, 84105, Beer Sheva, Israel.
Nanomicro Lett. 2021 Apr 20;13(1):112. doi: 10.1007/s40820-021-00610-w.
Novel artificial nose based upon electrode-deposited carbon dots (C-dots). Significant selectivity and sensitivity determined by "polarity matching" between the C-dots and gas molecules. The C-dot artificial nose facilitates, for the first time, real-time, continuous monitoring of bacterial proliferation and discrimination among bacterial species, both between Gram-positive and Gram-negative bacteria and between specific strains. Machine learning algorithm furnishes excellent predictability both in the case of individual gases and for complex gas mixtures. Continuous, real-time monitoring and identification of bacteria through detection of microbially emitted volatile molecules are highly sought albeit elusive goals. We introduce an artificial nose for sensing and distinguishing vapor molecules, based upon recording the capacitance of interdigitated electrodes (IDEs) coated with carbon dots (C-dots) exhibiting different polarities. Exposure of the C-dot-IDEs to volatile molecules induced rapid capacitance changes that were intimately dependent upon the polarities of both gas molecules and the electrode-deposited C-dots. We deciphered the mechanism of capacitance transformations, specifically substitution of electrode-adsorbed water by gas molecules, with concomitant changes in capacitance related to both the polarity and dielectric constants of the vapor molecules tested. The C-dot-IDE gas sensor exhibited excellent selectivity, aided by application of machine learning algorithms. The capacitive C-dot-IDE sensor was employed to continuously monitor microbial proliferation, discriminating among bacteria through detection of distinctive "volatile compound fingerprint" for each bacterial species. The C-dot-IDE platform is robust, reusable, readily assembled from inexpensive building blocks and constitutes a versatile and powerful vehicle for gas sensing in general, bacterial monitoring in particular.
基于电极沉积碳点(C点)的新型人工鼻。其显著的选择性和灵敏度由C点与气体分子之间的“极性匹配”决定。C点人工鼻首次实现了对细菌增殖的实时、连续监测以及对细菌种类的区分,包括革兰氏阳性菌与革兰氏阴性菌之间以及特定菌株之间的区分。机器学习算法在单个气体以及复杂气体混合物的情况下都具有出色的可预测性。尽管是难以实现的目标,但通过检测微生物释放的挥发性分子来对细菌进行连续、实时监测和识别备受关注。我们介绍了一种用于传感和区分蒸汽分子的人工鼻,它基于记录涂有具有不同极性的碳点(C点)的叉指电极(IDE)的电容。将C点-IDE暴露于挥发性分子会引起快速的电容变化,这些变化密切依赖于气体分子和电极沉积的C点的极性。我们解读了电容转换的机制,特别是气体分子取代电极吸附的水,同时伴随着与所测试蒸汽分子的极性和介电常数相关的电容变化。借助机器学习算法,C点-IDE气体传感器表现出出色的选择性。电容式C点-IDE传感器用于连续监测微生物增殖,通过检测每种细菌独特的“挥发性化合物指纹”来区分细菌。C点-IDE平台坚固耐用、可重复使用,由廉价组件易于组装而成,总体上构成了一种通用且强大的气体传感工具,尤其适用于细菌监测。